DOSPERT_raw

A data.frame containing responses to the risk subscale of the Domain Specific
Risk Taking Scale (DOSPERT; Weber, Blais, &amp; Betz, 2002) based on the publicly
available dataset (at <a href="https://osf.io/pjt57/">https://osf.io/pjt57/</a>) by Frey, Duncan, and Weber (2020).
The items measure risk-taking propensity on six different domains: social,
recreational, gambling, health/ safety, investment, and ethical.

datasets

Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.

Markus Steiner

EFAtools

Fast and Flexible Implementations of Exploratory Factor Analysis
Tools

DOSPERT_raw function

An object of class <code>data.frame</code> with 3123 rows and 30 columns.

Format

A data.frame containing responses to the risk subscale of the Domain Specific
Risk Taking Scale (DOSPERT; Weber, Blais, &amp; Betz, 2002) based on the publicly
available dataset (at <a href='https://osf.io/pjt57/'>https://osf.io/pjt57/</a>) by Frey, Duncan, and Weber (2020).
The items measure risk-taking propensity on six different domains: social,
recreational, gambling, health/ safety, investment, and ethical.

DOSPERT_raw: DOSPERT_raw

Description

Usage

Arguments

Format